Course

Model Training Deep Dive: Setup

Are you ready to take your data management skills to the next level? Our comprehensive course on data structures, permissions, and setting up datasets is here to help!
  • 9963 enrolled students
  • December 18, 2023
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Model Training Deep Dive: Setup

  • 00:30:00
  • Downloadable resources available
  • Diploma of Completion included
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Course details

Difficulty Level

Beginner

Language

English

Completion time

00:30:00

Product covered

UiPath Communications Mining

About the Model Training Deep Dive: Setup course 

This course is meant to provide technical audiences and business users with an understanding of data structures, permissions, and setting up datasets.  

This course covers creating a new dataset, importing your taxonomy, enabling and creating entities, and understanding the status of your dataset. 

The Model Training Deep Dive: Setup course takes 30 minutes to complete. At the end, you’ll receive a diploma of completion. 

 

Course prerequisites 

To enjoy this learning experience, we recommend you going through the following courses: 

  • UiPath Communications Mining Overview 
  • Fundamentals of Model Training 
  • Taxonomy Design 

 

Course audience 

The Model Training Deep Dive: Setup course is aimed at technical audiences and business users, as well as anybody else curious to see the power of Natural Language Processing in business. 

 

The Model Training Deep Dive: Setup course agenda 

The full agenda covers:  

  • Managing Datasets 
  • Importing Taxonomy 
  • Dataset Training status 
  • Practice: Set Up a Dataset Ready for Training 

 

Model Training Deep Dive: Setup course learning objectives 

At the end of the Model Training Deep Dive: Setup course, you should be able to: 

  • Explain the data structure and permissions in Communications Mining. 
  • Create a new dataset. 
  • Enable entities on a dataset. 
  • Import your taxonomy from a spreadsheet via the 'Settings' or 'Train' pages. 
  • Describe how the platform re-trains during model training. 
  • Explain the status of your dataset.